Overview
Clean, analyze, and prepare data for real-world machine learning and AI applications., Build and evaluate machine learning models for regression, classification, clustering, and recommendation systems., Apply deep learning techniques such as neural networks, CNNs, RNNs, and generative AI for advanced use cases., Work confidently with Python, Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch to solve end-to-end problems, Perform feature engineering, model optimization, and hyperparameter tuning to improve accuracy, Deploy models into production using APIs (FastAPI, Flask), Docker, and Streamlit dashboards., Understand the basics of MLOps, including model monitoring, performance tracking, and drift detection., Tackle real-world projects and a capstone, gaining the confidence to showcase a complete portfolio to employers., Translate technical outputs into business insights and decision-making strategies., Prepare for career roles like Data Scientist, Machine Learning Engineer, or AI Specialist.
Beginners in Data Science & AI who want a structured, step-by-step path to mastery., Students and recent graduates looking to gain practical skills and build a strong project portfolio., Professionals in IT, software engineering, or business analytics who want to transition into data science and machine learning roles., Working data analysts who want to upgrade from basic analytics to machine learning and AI applications., Career changers from non-technical backgrounds who are motivated to learn programming and data-driven problem solving, Entrepreneurs and innovators who want to apply AI techniques to real-world challenges and startup ideas., Anyone passionate about hands-on learning, real-world case studies, and building job-ready skills in a fast-growing field.
Basic computer literacy – comfort with installing software, navigating files, and using online tools., Familiarity with mathematics fundamentals – especially algebra, probability, and basic statistics (no advanced math required)., Beginner-level Python knowledge – understanding variables, loops, functions, and simple data structures., A computer with Windows, macOS, or Linux and internet connection to run tools and complete labs., Curiosity, persistence, and a willingness to learn by doing—no prior machine learning or AI experience required.
“This course contains the use of artificial intelligence.”
This comprehensive Data Science and Artificial Intelligence Mastery course is designed to take you from beginner to job-ready professional in just 100 days. Through a carefully structured curriculum, you’ll gain both theoretical knowledge and hands-on experience with the most in-demand tools and technologies in the industry.
You’ll begin by building a strong foundation in data analysis, data cleaning, and feature engineering, learning how to work with structured and unstructured data. From there, you’ll dive deep into machine learning algorithms such as regression, classification, and clustering, while also mastering advanced topics like deep learning, neural networks, and generative AI.
Every step of the way, you’ll reinforce your skills with hands-on labs, real-world case studies, and a capstone project that simulates industry challenges. You’ll also explore data visualization, model deployment with APIs (FastAPI, Flask), and MLOps concepts like monitoring and drift detection, preparing you for the realities of production environments.
By the end of this course, you’ll have a polished portfolio showcasing end-to-end AI projects, a deep understanding of tools such as Python, Pandas, Scikit-Learn, TensorFlow, PyTorch, Docker, and Streamlit, and the confidence to apply for roles like Data Scientist, Machine Learning Engineer, or AI Specialist.
This isn’t just a course—it’s a complete career preparation journey, giving you the skills, projects, and confidence to stand out in today’s competitive data-driven job market.
Data Science Academy
Data Science Academy is a leading provider of practical, industry-focused training in data analytics, data science, and business intelligence. With a mission to make data skills accessible to everyone, the academy designs courses that bridge the gap between theory and real-world application.
Our team of expert instructors brings years of professional experience from diverse industries, including technology, finance, healthcare, and aviation. We specialize in creating hands-on learning experiences that cover the full data lifecycle—from data collection and cleaning to analysis, visualization, and storytelling.
At Data Science Academy, we believe in learning by doing. Our courses feature step-by-step projects, interactive exercises, and real-world datasets, enabling learners to build job-ready skills in Excel, SQL, Python, Power BI, Tableau, and other leading tools.
We are passionate about empowering students to turn raw data into actionable insights that drive decision-making. Whether you are a beginner exploring data for the first time or a professional looking to upgrade your skill set, our courses are designed to help you succeed in today’s data-driven world.
Recent training programs from Data Science Academy include Python for Data Analysis, SQL for Business Intelligence, and Data Visualization with Power BI—all crafted to prepare learners for real-world analytics roles.